Model updating for developed calibrations is critical for robust spectral analysis in fruit quality control. Existing methods have limitations that usually need sufficient samples for model recalibration and are mainly designed for conventional linear models. This study proposes a model fine-tuning approach to update nonlinear deep learning models using limited sample sizes for fruit detection under interseason...
Made available in DSpace on 2020-12-11T01:57:28Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-10-29; Griffith University Gowonda HPC Cluster; Queensland Cyber Infrastructure Foundation; Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents tha...